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American interview questions
5 practice questions in the style of American's interviews, covering Coding & Algorithms, Software Engineering Fundamentals, ML System Design.
1 easy4 medium0 hard
American interview questions by the numbers
Last updated
Katkat has 5 American interview questions. The largest topics are Coding & Algorithms (40%), Software Engineering Fundamentals (40%) and ML System Design (20%). By difficulty: 20% easy and 80% medium. The most common round is Online Assessment (60%). Frequent concepts include Backtracking, Bipartite Matching, Clean Code and Data Structures.
Topics
- Coding & Algorithms40% · 2
- ML System Design20% · 1
Difficulty
- Easy20% · 1
- Medium80% · 4
Interview rounds
- Online Assessment60% · 3
- Technical Screen40% · 2
Roles
- Software Engineer80% · 4
- Machine Learning Engineer20% · 1
Frequent concepts
- Backtracking20% · 1
- Bipartite Matching20% · 1
- Clean Code20% · 1
- Data Structures20% · 1
- Debugging20% · 1
- Design Patterns20% · 1
Most mentioned in interview experiences
- 1.Cover the Most Points with an Axis-Aligned Rectangle of Bounded Perimeter1 report
- 2.Spread Nine Stones Across a Three-by-Three Grid with Minimum Moves1 report
- 3.Structure a Pizza-Ordering System with Four Discount Policies1 report
Counted from 1 candidate interview experiences on Katkat. How we collect and count
Showing 1–5 of 5 results
Maximize point coverage with an axis-aligned rectangle under a perimeter budget, including boundary points and repeated coordinates.
AmericanSoftware EngineerCoding & AlgorithmsOnline AssessmentThis problem tests your ability to identify state synchronization issues in nested class structures and implement a thread-safe extension to existing class logic.
AmericanSoftware EngineerSoftware Engineering FundamentalsTechnical ScreenThis question evaluates a candidate's competency in ML system design for enterprise retrieval-augmented generation and agent architectures, covering understanding of model roles, agent tool integrations, memory and state design, evaluation metrics, security and privacy defenses, concurrency and reliability, workflow durability, and document ingestion/indexing challenges. It is commonly asked in ML system design interviews to assess architectural thinking and trade-off analysis, testing both conceptual understanding and practical application skills for building scalable, secure, and cost-effective enterprise AI assistants.
AmericanMachine Learning EngineerML System DesignTechnical ScreenCalculate the minimum number of orthogonal moves needed to distribute stones so that every cell in a 3x3 grid contains exactly one stone.
AmericanSoftware EngineerCoding & AlgorithmsOnline AssessmentDesign an extensible object-oriented order pricing system for a pizzeria that models pizzas, applies four distinct discount policies with specific composition rules, and returns an itemized, explainable receipt.
AmericanSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
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